O89020 Afamin MolNFT, Molecular NFT on GenesisL1

Afamin

MOLNFT AF v1 smart contract in GenesisL1 blockchain:

0xBf7491af3407816DFa88a5EA4c82e8A2B1D721eD

IPFS of NFT metadata:

bafybeid6rdw6tcyx3ynsvfvagyk3zhx5yeqmc6iauzzxmwfbeb2pgabunu/metadata.json

IPFS of structure file:

bafybeigidlovfnnq5ku5fdsykwpztmawhvpusm75h4lslxkmlc6r5gap54/AF-O89020-F1-model_v2.pdb

First NFT owner address (eip-55):

0x659f8B68Cf71AE0752415b7f448AB83B3c5c37EA

First NFT owner address (bech32):

genesis1vk0ck6x0wxhqw5jptdl5fz4c8v79cdl2mraal6

Current NFT ID #10894 owner (web3):

0xffcCCa7Da70F32A6f766185797d8A09ea11e0830

First owner GALLERY | EVM EXPLORER | COSMOS EXPLORER

MOLNFT AF v1

NFT id:
10894
Accession (UniProt):
O89020
Name::
Afamin
Experimental Method:
Predicted structure
Sequence source:
MUS MUSCULUS

NFT data

MolNFT AF v1 is an AlphaFold database of AI predicted Swiss-Prot protein sequences preserved as regular ERC-721 NFT tokens on GenesisL1 blockchain for public free use, research and entertainment:

https://alphafold.ebi.ac.uk/
Jumper, J., Evans, R., Pritzel, A. et al. Highly accurate protein structure prediction with AlphaFold. 
Nature 596, 583–589 (2021). https://doi.org/10.1038/s41586-021-03819-2

MOLNFT O89020 research and analysis (ICN3D with VR)

FASTA sequences

>sp|O89020|AFAM_MOUSE Afamin OS=Mus musculus OX=10090 GN=Afm PE=1 SV=2 MRHLKLTGFIFFLLPLTESLALPTKPQDVDHFNATQKFIDENTTYLAIIAFSQYVQEASFDEVETLVKVMLDYRDRCWADNTLPECSKTANDAIQDMLCDMEGLPQKHNFSHCCGKAGFPRRLCFFYNKKANVGFLPPFPTLDPEEKCQAYKNNSESFLHLYMYEVARRNPFVFAPVLLAVAAWFEEAATTCCEQQQKATCFQAKAAPITQYLKASSSYQRNVCGALIKFGPKVLNSINVAVFSKKFPKIGFKDLTTLLEDVSSMYEGCCEGDVVHCIRSQSQVVNHICSKQDSISSKIKVCCEKKTLEREACIINANKDDRPEGLSLREAKFTESENVCQERDSDPDKFFAEFIYEYSRRHPDLSTPELLRITKVYMDFLEDCCSRENPAGCYRHVEDKFNETTQRSLAMVQQECKQFQELGKDTLQRHFLVKFTKAAPQLPMEELVSLSKEMVAALTTCCTLSDEFACVDNLADLVLGELCGVNTNRTINPAVDHCCKTDFAFRRHCFEHLKADTTYELPSVSALVSALHTDWCQPRKEDLQNKKHRFLVNLVKWMPGITDEEWLCLFTKFTAAREECSEVQEPESCFSPESSKTGDESQATEKQR

O89020 AF NFT

MOLNFT AF v1

NFT data

MOLNFT O89020 research and analysis (ICN3D with VR)

FASTA sequences

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